Introduction
The challenge enterprises face is adopting new technologies to manage data. But, even more importantly, using the latest technologies is not a solution by itself, and companies should think first about adding value to the organization through data. Research shows that 61% of Chief Data Officers want to deliver their data strategy as one of their top three priorities.
Business pivot moments setting the stage for data strategy
What is the perfect time to consider building a data strategy? Ideally, a data strategy can be set up as the company grows early. However, if your enterprise is not in the data industry, other business development priorities exist.
Once your business reaches an important milestone or hits a critical business moment, it could be an appropriate time to start working on an effective data strategy. Such moments can come from:
- Entering new markets
- Launching new products
- Acquisition and merger
- Growth in sales or scaling up the business
In highly competitive industries, every detail that can become an asset or bring added value should be considered. Businesses in transformation, growth, or other pivotal moments can look for data strategy as a value proposition that can accelerate or help with the positive trajectory.
Aligning data strategy with company policy and targets
Businesses facing pivotal moments can experience dramatic changes in strategy, targets, and overall goals. Even personnel change can set a new course for the company. In today‚s rapidly changing environment, every organization should review and adjust its business strategy within three to five years.
Once the organization decides on the new course or improves the existing structure, it is time to consider a data strategy to support these changes with appropriate use of data. A straightforward example of how data can help businesses is helping management make informed decisions from the analysis of data sets.
What should a company look for in data strategy?
Creating a comprehensive data strategy has several potential pitfalls. From a technocratic perspective, a company can implement state-of-the-art technical solutions, and it could be hard to criticize that decision. However, if it doesn’t align with the business strategy and goals, the solution itself will not make a difference.
Key stakeholders for data strategy should think about a value-driven approach that focuses on outcomes rather than implementing the latest eye-candy solution industry praises.
Adding value is an easy layout goal, but how can a company effectively go in that direction? As a Chief Data Officer, you can ask yourself several questions. Most importantly, are there business benefits from planned data management technology and strategy?
Other key questions are:
- How does data strategy align with company strategy?
- Will it fit the workflow and company procedures?
- Can it be implemented quickly, and can the company scale up effortlessly?
Finally, in value-driven data strategy, the keyword is value. You have to always ask yourself, what is the value of implementing a data strategy?
Driving transformation with a unique data strategy approach
Most businesses face a challenge to get to the perceived next level or grow beyond pivotal business moments. Creating a data strategy can be that catalyzation. A quality approach combines the latest tech trends with a grain of salt. Salt, in this case, is a data strategy that adds value.
Creating a comprehensive data strategy driven by value focuses on outcomes and measurable benefits that can elevate business, not just satisfy having data taken care of as a task.
Your organization should look for value-oriented outcomes like:
- Revenue Growth: Revenue is the bloodstream of all businesses. Data strategy should drive sales, expand market share, or open new revenue streams.
- Cost Savings: Can data strategy detect inefficient workflow or practice in the company, optimize resources, or lower operating costs?
- Improving efficiency: Can your organization use data to streamline processes, automate tasks, and become more agile?
- Risk Mitigation: How can data help your company manage risk, ensure regulatory compliance, or help with decision-making processes to avoid costly errors?
Depending on the industry, companies can look for other beneficial outcomes. All of these can help meaningfully and transform data strategy into an invaluable asset. Data can show inefficient ways of managing warehouse or transport routes, which can lead to reducing costs.
Handling documents and invoices may go through one too many hands, and automating document management can improve speed, relieve administrative costs, and help employees focus on core business more effectively.
A value-driven data strategy with effective analysis can show metrics like what customers like the most, seasonal trends, or other vital data that can drive sales or expand market share.
Each industry has specific ways to use data, and outcome-optimized value data strategy will find those clues and turn them into palpable benefits.
Understanding the business ins and outs is crucial for effective data strategy
Unlike taking an off-the-shelf data management solution, creating an effective data strategy requires a deep understanding of the business with clear goals, pain points, and growth opportunities. When implementing data solutions, thinking as a business leader is essential, and the choice of technology comes from that mindset as a second thing in the queue.
You are ready to go if you look for outcomes like revenue growth, cost savings, better efficiency, and risk mitigation with the help of data.
How will you know if the data strategy is working? Some or all goals will come to fruition, and a quality, value-driven data strategy will drive transformation. Companies that don’t get such results will have to do things differently.
Data officers should strive to challenge the status quo and focus on positive outcomes to start the transformation journey.
My mission is to change your life in how you make everyday decisions based on proper data.
I do this by helping corporate data leaders create and adopt data strategies built on Microsoft platforms using artificial intelligence. Over my 15+ year career, I have gained experience which I use to mentor clients and pass on to the community as a speaker and data leader in the industry.